智能系统学报2024，Vol.19Issue(6)：1562-1572,11.DOI:10.11992/tis.202404009
采用目标注意力的方面级多模态情感分析研究
Aspect-level multimodal sentiment analysis via object-attention
摘要
Abstract
Aspect-level multimodal sentiment analysis(ALMSA)aims to identify the sentiment polarity of a specific as-pect word using both sentence and image data.Current models often rely on the global features of images,overlooking the details in the original image.To address this issue,we propose an object attention-based aspect-level multimodal sentiment analysis model(OAB-ALMSA).This model first employs an object detection algorithm to capture the de-tailed information of the objects from the original image.It then applies an object-attention mechanism and builds an it-erative fusion layer to fully fuse the multimodal information.Finally,a curriculum learning strategy is developed to tackle the challenges of training with complex samples.Experiments conducted on TWITTER-2015 data sets demon-strate that OAB-ALMSA,when combined with curriculum learning,achieves the highest F1.These results highlight that leveraging detailed image data enhances the model's overall understanding and improves prediction accuracy.关键词
方面级情感分析/多模态/情感分析/目标检测/自注意力机制/自然语言处理/深度学习/特征提取Key words
aspect-level sentiment analysis/multimodal/sentiment analysis/object detection/self-attention/natural lan-guage processing systems/deep learning/feature extraction分类
计算机与自动化引用本文复制引用
朱超杰,闫昱名,初宝昌,李刚,黄河燕,高小燕..采用目标注意力的方面级多模态情感分析研究[J].智能系统学报,2024,19(6):1562-1572,11.基金项目
国家自然科学基金项目(U21B2009) （U21B2009）
横向科技项目(2023110051000823). （2023110051000823）
